Elsevier, a world-leading provider of scientific, technical and medical information products and services, today announced the publication of Machine Learning: A Bayesian and Optimization Perspective by signal processing expert Dr. Sergios Theodoridis. This book provides an in-depth understanding of all primary machine learning methods. It will be featured, along with two other new communications engineering books, in Elsevier’s booth # 10 at the 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015 held in Brisbane, Australia, April 19-24.

Machine Learning presents the major machine learning methods developed in different disciplines, such as statistics, computer science, and statistical and adaptive signal processing. Focusing on the physical reasoning behind the mathematics, the various methods and techniques are explained in depth, supported by examples and problems. The book builds carefully from the basic classical methods to the most recent trends. It is suitable for courses on pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, sparse modeling, deep learning and probabilistic graphical models.

Dr. Theodoridis is Professor of Signal Processing and Machine Learning in the Department of Informatics and Telecommunications at the University of Athens, Greece. He co-authored the bestselling book, Pattern Recognition, as well as Introduction to Pattern Recognition: A MATLAB Approach. Dr. Theodoridis serves as editor-in-chief of IEEE Transactions on Signal Processing and as co-editor- in-chief for Elsevier’s Academic Press Library in Signal Processing. His numerous awards include the 2014 IEEE Signal Processing Magazine Best Paper Award, the 2014 IEEE Signal Processing Society Education Award, and the EURASIP 2014 Meritorious Service Award.

The books are available on the Elsevier Store and on ScienceDirect, Elsevier’s full-text scientific database offering journal articles and book chapters from over 2,500 peer-reviewed journals and more than 33,000 book titles.

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Notes for EditorsReview copies of the books are available to credentialed journalists upon request. Contact Michelle McMahon at m.mcmahon.1@elsevier.com or +1 781 663 2268.

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